Nectar Microbiome

Study is blah.

They found blah.

nectar <- readRDS("./data/bacteria_phyloseq.RDS")
nectar.sample_data <- nectar@sam_data %>% 
  add_count(Treatment) %>% 
  mutate(Treatment_n = paste0(Treatment, " (", n, ")"))

if (!file.exists("./data/jrbp.map.rds"))
{
  jrbp.map <- get_map(location = c(lon = mean(nectar.sample_data$longitude), 
                                   lat = mean(nectar.sample_data$latitude)), zoom = 17, 
                      maptype = "satellite", scale = 2)
  saveRDS(jrbp.map, "./data/jrbp.map.rds")
} else {
  jrbp.map <- readRDS("./data/jrbp.map.rds")
}

Getting the map

ggplotly(jrbp.plot, 
         tooltip = c("latitude", "longitude", "treatment"))
nectar.homology <- get_homology_from_phyloseq(nectar)
plot_barcode(nectar.homology) + 
  labs(x = "Nectar") +
  xlim(0, 4) + 
  theme(axis.text = element_blank(), axis.ticks = element_blank(),
        legend.position = "none")
## Scale for 'x' is already present. Adding another scale for 'x', which
## will replace the existing scale.

Want to do persistent homology to see what’s up.

Permutation tests

nectar.by_treatment.bray <- get_persistence_list(nectar, "Treatment")
if (!file.exists("./data/nectar.bray.perm_tests")){
  nectar.bray.perm_tests <- get_pairwise_permutation_tests(nectar.by_treatment.bray, 
                                                           iters = 1500)
  saveRDS(nectar.bray.perm_tests, "./data/nectar.bray.perm_tests")
} else {
  nectar.bray.perm_tests <- readRDS("./data/nectar.bray.perm_tests")
}
get_dimension_heatmap(nectar.bray.perm_tests, dimension = 1, triangle = TRUE) +   
  labs(title = "Dimension 1", subtitle = element_blank()) +
  theme(plot.title = element_text(hjust = 0.5), legend.position = "none")

get_dimension_heatmap(nectar.bray.perm_tests, dimension = 2, triangle = TRUE) + 
  labs(title = "Dimension 2", subtitle = element_blank()) +
  theme(plot.title = element_text(hjust = 0.5)) 

plot_barcode(nectar.by_treatment.bray$Exposed$hom) + 
  labs(colour = "", x = "Exposed") + 
  theme(axis.text = element_blank(), axis.ticks = element_blank(),
        legend.position = "none")

Sample

angles <- runif(100, 0, 2 * pi)
circ.2d <- cbind(cos(angles), sin(angles))
ggplot(as.data.frame(circ.2d)) + geom_point(aes(x = as.data.frame(circ.2d)[,1], y = as.data.frame(circ.2d)[, 2]))+
  labs(x = "", y = "") + 
  theme(axis.text.x = element_blank(), axis.text.y = element_blank(), axis.ticks = element_blank())

circ.hom <- calculate_homology(circ.2d, dim = 1)
plot_barcode(circ.hom) +
  labs(x = element_blank()) +  
  theme(axis.text = element_blank(), axis.ticks = element_blank(),
        legend.position = "none")

get_landscape(circ.hom, d = 0, max_x = 0.5) + 
  labs(title = "Test")



Paul Villanueva
Ph.D. Student - Bioinformatics and Computational Biology
Iowa State University, Ames, IA.